Overview

Dataset statistics

Number of variables12
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory112.3 B

Variable types

Categorical2
Numeric10

Dataset

Description근로복지공단에서 산재로 승인(일부승인 포함)된 현황입니다.
Author근로복지공단
URLhttps://www.data.go.kr/data/15084505/fileData.do

Alerts

2016년 신청 is highly overall correlated with 2016년 승인 and 8 other fieldsHigh correlation
2016년 승인 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2017년 신청 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2017년 승인 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2018년 신청 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2018년 승인 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2019년 신청 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2019년 승인 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2020년 신청 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2020년 승인 is highly overall correlated with 2016년 신청 and 8 other fieldsHigh correlation
2016년 신청 has unique valuesUnique
2016년 승인 has unique valuesUnique
2017년 신청 has unique valuesUnique
2017년 승인 has unique valuesUnique
2018년 신청 has unique valuesUnique
2018년 승인 has unique valuesUnique
2019년 신청 has unique valuesUnique
2019년 승인 has unique valuesUnique
2020년 신청 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:18:35.894003
Analysis finished2023-12-12 00:18:46.305264
Duration10.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
전국
7 
경상북도
7 
구미시
7 

Length

Max length4
Median length3
Mean length3
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전국
2nd row전국
3rd row전국
4th row전국
5th row전국

Common Values

ValueCountFrequency (%)
전국 7
33.3%
경상북도 7
33.3%
구미시 7
33.3%

Length

2023-12-12T09:18:46.383818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:46.498603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전국 7
33.3%
경상북도 7
33.3%
구미시 7
33.3%

연령
Categorical

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
10대
3 
20대
3 
30대
3 
40대
3 
50대
3 
Other values (2)
6 

Length

Max length6
Median length3
Mean length3.4285714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10대
2nd row20대
3rd row30대
4th row40대
5th row50대

Common Values

ValueCountFrequency (%)
10대 3
14.3%
20대 3
14.3%
30대 3
14.3%
40대 3
14.3%
50대 3
14.3%
60대 3
14.3%
70대 이상 3
14.3%

Length

2023-12-12T09:18:46.628320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:46.772202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10대 3
12.5%
20대 3
12.5%
30대 3
12.5%
40대 3
12.5%
50대 3
12.5%
60대 3
12.5%
70대 3
12.5%
이상 3
12.5%

2016년 신청
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5118.5238
Minimum12
Maximum31742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:46.894346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile18
Q1126
median1084
Q33794
95-th percentile20718
Maximum31742
Range31730
Interquartile range (IQR)3668

Descriptive statistics

Standard deviation8655.6682
Coefficient of variation (CV)1.6910478
Kurtosis3.7267291
Mean5118.5238
Median Absolute Deviation (MAD)997
Skewness2.0490029
Sum107489
Variance74920592
MonotonicityNot monotonic
2023-12-12T09:18:47.043579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1084 1
 
4.8%
8573 1
 
4.8%
18 1
 
4.8%
120 1
 
4.8%
279 1
 
4.8%
172 1
 
4.8%
126 1
 
4.8%
69 1
 
4.8%
12 1
 
4.8%
346 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
12 1
4.8%
18 1
4.8%
69 1
4.8%
87 1
4.8%
120 1
4.8%
126 1
4.8%
172 1
4.8%
279 1
4.8%
346 1
4.8%
805 1
4.8%
ValueCountFrequency (%)
31742 1
4.8%
20718 1
4.8%
18122 1
4.8%
13219 1
4.8%
8573 1
4.8%
3794 1
4.8%
3132 1
4.8%
1992 1
4.8%
1819 1
4.8%
1260 1
4.8%

2016년 승인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4596.1429
Minimum12
Maximum28562
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:47.172085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile15
Q1113
median1051
Q32858
95-th percentile18751
Maximum28562
Range28550
Interquartile range (IQR)2745

Descriptive statistics

Standard deviation7783.3797
Coefficient of variation (CV)1.6934591
Kurtosis3.7324961
Mean4596.1429
Median Absolute Deviation (MAD)966
Skewness2.0473949
Sum96519
Variance60581000
MonotonicityNot monotonic
2023-12-12T09:18:47.298658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1051 1
 
4.8%
8133 1
 
4.8%
15 1
 
4.8%
108 1
 
4.8%
263 1
 
4.8%
154 1
 
4.8%
113 1
 
4.8%
65 1
 
4.8%
12 1
 
4.8%
239 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
12 1
4.8%
15 1
4.8%
65 1
4.8%
85 1
4.8%
108 1
4.8%
113 1
4.8%
154 1
4.8%
239 1
4.8%
263 1
4.8%
771 1
4.8%
ValueCountFrequency (%)
28562 1
4.8%
18751 1
4.8%
15805 1
4.8%
12110 1
4.8%
8133 1
4.8%
2858 1
4.8%
2803 1
4.8%
1824 1
4.8%
1625 1
4.8%
1172 1
4.8%

2017년 신청
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5155.0952
Minimum5
Maximum31080
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:47.462701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile20
Q1137
median1066
Q34792
95-th percentile20250
Maximum31080
Range31075
Interquartile range (IQR)4655

Descriptive statistics

Standard deviation8593.9329
Coefficient of variation (CV)1.6670755
Kurtosis3.3796523
Mean5155.0952
Median Absolute Deviation (MAD)975
Skewness1.9898245
Sum108257
Variance73855682
MonotonicityNot monotonic
2023-12-12T09:18:47.672067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1066 1
 
4.8%
8957 1
 
4.8%
20 1
 
4.8%
137 1
 
4.8%
253 1
 
4.8%
163 1
 
4.8%
120 1
 
4.8%
91 1
 
4.8%
5 1
 
4.8%
449 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
5 1
4.8%
20 1
4.8%
81 1
4.8%
91 1
4.8%
120 1
4.8%
137 1
4.8%
163 1
4.8%
253 1
4.8%
449 1
4.8%
857 1
4.8%
ValueCountFrequency (%)
31080 1
4.8%
20250 1
4.8%
19544 1
4.8%
12404 1
4.8%
8957 1
4.8%
4792 1
4.8%
3080 1
4.8%
1933 1
4.8%
1863 1
4.8%
1112 1
4.8%

2017년 승인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4618.9048
Minimum5
Maximum28101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:47.808518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile17
Q1124
median1030
Q33371
95-th percentile17837
Maximum28101
Range28096
Interquartile range (IQR)3247

Descriptive statistics

Standard deviation7741.0237
Coefficient of variation (CV)1.6759436
Kurtosis3.4390185
Mean4618.9048
Median Absolute Deviation (MAD)944
Skewness1.9982049
Sum96997
Variance59923448
MonotonicityNot monotonic
2023-12-12T09:18:47.965333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1031 1
 
4.8%
8496 1
 
4.8%
17 1
 
4.8%
124 1
 
4.8%
232 1
 
4.8%
147 1
 
4.8%
115 1
 
4.8%
86 1
 
4.8%
5 1
 
4.8%
311 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
5 1
4.8%
17 1
4.8%
78 1
4.8%
86 1
4.8%
115 1
4.8%
124 1
4.8%
147 1
4.8%
232 1
4.8%
311 1
4.8%
816 1
4.8%
ValueCountFrequency (%)
28101 1
4.8%
17837 1
4.8%
17563 1
4.8%
11393 1
4.8%
8496 1
4.8%
3371 1
4.8%
2838 1
4.8%
1710 1
4.8%
1696 1
4.8%
1031 1
4.8%

2018년 신청
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6012.9048
Minimum7
Maximum35750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:48.114588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile18
Q1139
median1069
Q35510
95-th percentile24151
Maximum35750
Range35743
Interquartile range (IQR)5371

Descriptive statistics

Standard deviation9992.6484
Coefficient of variation (CV)1.6618671
Kurtosis3.1158454
Mean6012.9048
Median Absolute Deviation (MAD)1042
Skewness1.9395813
Sum126271
Variance99853022
MonotonicityNot monotonic
2023-12-12T09:18:48.263454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
985 1
 
4.8%
11256 1
 
4.8%
18 1
 
4.8%
139 1
 
4.8%
307 1
 
4.8%
212 1
 
4.8%
132 1
 
4.8%
87 1
 
4.8%
7 1
 
4.8%
460 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
7 1
4.8%
18 1
4.8%
82 1
4.8%
87 1
4.8%
132 1
4.8%
139 1
4.8%
212 1
4.8%
307 1
4.8%
460 1
4.8%
985 1
4.8%
ValueCountFrequency (%)
35750 1
4.8%
24151 1
4.8%
22158 1
4.8%
14877 1
4.8%
11256 1
4.8%
5510 1
4.8%
3504 1
4.8%
2176 1
4.8%
2111 1
4.8%
1280 1
4.8%

2018년 승인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5503.5238
Minimum7
Maximum32967
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:48.394323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile18
Q1128
median1022
Q34311
95-th percentile21471
Maximum32967
Range32960
Interquartile range (IQR)4183

Descriptive statistics

Standard deviation9171.7927
Coefficient of variation (CV)1.6665309
Kurtosis3.1638094
Mean5503.5238
Median Absolute Deviation (MAD)941
Skewness1.9440627
Sum115574
Variance84121782
MonotonicityNot monotonic
2023-12-12T09:18:48.538350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
950 1
 
4.8%
10756 1
 
4.8%
18 1
 
4.8%
128 1
 
4.8%
290 1
 
4.8%
195 1
 
4.8%
121 1
 
4.8%
86 1
 
4.8%
7 1
 
4.8%
363 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
7 1
4.8%
18 1
4.8%
78 1
4.8%
86 1
4.8%
121 1
4.8%
128 1
4.8%
195 1
4.8%
290 1
4.8%
363 1
4.8%
950 1
4.8%
ValueCountFrequency (%)
32967 1
4.8%
21471 1
4.8%
20482 1
4.8%
13964 1
4.8%
10756 1
4.8%
4311 1
4.8%
3246 1
4.8%
1963 1
4.8%
1949 1
4.8%
1207 1
4.8%

2019년 신청
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6545.8571
Minimum6
Maximum38031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:48.682391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile29
Q1172
median1117
Q36535
95-th percentile27467
Maximum38031
Range38025
Interquartile range (IQR)6363

Descriptive statistics

Standard deviation10793.005
Coefficient of variation (CV)1.6488299
Kurtosis2.8527243
Mean6545.8571
Median Absolute Deviation (MAD)1036
Skewness1.8936822
Sum137463
Variance1.1648896 × 108
MonotonicityNot monotonic
2023-12-12T09:18:48.846971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
958 1
 
4.8%
12790 1
 
4.8%
29 1
 
4.8%
172 1
 
4.8%
293 1
 
4.8%
211 1
 
4.8%
128 1
 
4.8%
96 1
 
4.8%
6 1
 
4.8%
687 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
6 1
4.8%
29 1
4.8%
81 1
4.8%
96 1
4.8%
128 1
4.8%
172 1
4.8%
211 1
4.8%
293 1
4.8%
687 1
4.8%
958 1
4.8%
ValueCountFrequency (%)
38031 1
4.8%
27467 1
4.8%
23149 1
4.8%
16058 1
4.8%
12790 1
4.8%
6535 1
4.8%
3513 1
4.8%
2746 1
4.8%
2082 1
4.8%
1314 1
4.8%

2019년 승인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5954.9524
Minimum6
Maximum34954
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:49.027026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile24
Q1166
median1071
Q34903
95-th percentile24222
Maximum34954
Range34948
Interquartile range (IQR)4737

Descriptive statistics

Standard deviation9871.2362
Coefficient of variation (CV)1.6576516
Kurtosis2.8718361
Mean5954.9524
Median Absolute Deviation (MAD)996
Skewness1.8940327
Sum125054
Variance97441305
MonotonicityNot monotonic
2023-12-12T09:18:49.187747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
891 1
 
4.8%
12212 1
 
4.8%
24 1
 
4.8%
166 1
 
4.8%
277 1
 
4.8%
191 1
 
4.8%
124 1
 
4.8%
94 1
 
4.8%
6 1
 
4.8%
451 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
6 1
4.8%
24 1
4.8%
75 1
4.8%
94 1
4.8%
124 1
4.8%
166 1
4.8%
191 1
4.8%
277 1
4.8%
451 1
4.8%
891 1
4.8%
ValueCountFrequency (%)
34954 1
4.8%
24222 1
4.8%
21437 1
4.8%
15108 1
4.8%
12212 1
4.8%
4903 1
4.8%
3259 1
4.8%
2430 1
4.8%
1918 1
4.8%
1241 1
4.8%

2020년 신청
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6475.381
Minimum6
Maximum36049
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:49.325475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile31
Q1192
median1089
Q36792
95-th percentile28457
Maximum36049
Range36043
Interquartile range (IQR)6600

Descriptive statistics

Standard deviation10598.483
Coefficient of variation (CV)1.6367351
Kurtosis2.3582576
Mean6475.381
Median Absolute Deviation (MAD)1028
Skewness1.8121819
Sum135983
Variance1.1232784 × 108
MonotonicityNot monotonic
2023-12-12T09:18:49.454535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
767 1
 
4.8%
13106 1
 
4.8%
31 1
 
4.8%
192 1
 
4.8%
284 1
 
4.8%
194 1
 
4.8%
162 1
 
4.8%
84 1
 
4.8%
6 1
 
4.8%
626 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
6 1
4.8%
31 1
4.8%
61 1
4.8%
84 1
4.8%
162 1
4.8%
192 1
4.8%
194 1
4.8%
284 1
4.8%
626 1
4.8%
767 1
4.8%
ValueCountFrequency (%)
36049 1
4.8%
28457 1
4.8%
22733 1
4.8%
16017 1
4.8%
13106 1
4.8%
6792 1
4.8%
3326 1
4.8%
2793 1
4.8%
1879 1
4.8%
1335 1
4.8%

2020년 승인
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5893.6667
Minimum5
Maximum33102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:49.577100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile28
Q1179
median1040
Q35415
95-th percentile25156
Maximum33102
Range33097
Interquartile range (IQR)5236

Descriptive statistics

Standard deviation9659.2356
Coefficient of variation (CV)1.6389179
Kurtosis2.3646204
Mean5893.6667
Median Absolute Deviation (MAD)981
Skewness1.8093065
Sum123767
Variance93300832
MonotonicityNot monotonic
2023-12-12T09:18:49.732676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
179 2
 
9.5%
703 1
 
4.8%
3085 1
 
4.8%
28 1
 
4.8%
270 1
 
4.8%
152 1
 
4.8%
79 1
 
4.8%
5 1
 
4.8%
491 1
 
4.8%
2519 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
5 1
4.8%
28 1
4.8%
59 1
4.8%
79 1
4.8%
152 1
4.8%
179 2
9.5%
270 1
4.8%
491 1
4.8%
703 1
4.8%
1040 1
4.8%
ValueCountFrequency (%)
33102 1
4.8%
25156 1
4.8%
20905 1
4.8%
14911 1
4.8%
12478 1
4.8%
5415 1
4.8%
3085 1
4.8%
2519 1
4.8%
1759 1
4.8%
1252 1
4.8%

Interactions

2023-12-12T09:18:45.066737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.273056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.136331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.025160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.161141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.040591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.170336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.136995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.071129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.206025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.154237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.345164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.219123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.358357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.254614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.135202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.267203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.241782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.174779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.283734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.232535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.430797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.294667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.433829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.333611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.237669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.386214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.329740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.252154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.359026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.313686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.510114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.368649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.517720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.429896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.322230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.478704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.415140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.350125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.436042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.395277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.587138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.447853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.616857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.518649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.418556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.563069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.498312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.421075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.520634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.515682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.692162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.544174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.716387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.612590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.559061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.654795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.590650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.503069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.608177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.621432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.786554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.628377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.803941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.695297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.728503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.749859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.667421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.598308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.697844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.709205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.890698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.742828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.885228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.778126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.850132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.854480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.764839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.681094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.791913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.802699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:36.974660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.849137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:38.971879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.857367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:40.976176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.957529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.853281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.779104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.893404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:45.896801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.057115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:37.942117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.072799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:39.955251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:41.081764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.053873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:42.960488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:43.863739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:44.988170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:18:49.855522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분연령2016년 신청2016년 승인2017년 신청2017년 승인2018년 신청2018년 승인2019년 신청2019년 승인2020년 신청2020년 승인
구분1.0000.0000.5130.6120.7820.7330.7820.7820.5130.7820.5130.513
연령0.0001.0000.1880.1530.0000.0000.0000.0000.1880.0000.1880.188
2016년 신청0.5130.1881.0001.0001.0000.9591.0001.0001.0001.0001.0001.000
2016년 승인0.6120.1531.0001.0000.9910.9910.9910.9911.0000.9911.0001.000
2017년 신청0.7820.0001.0000.9911.0000.9981.0001.0001.0001.0001.0001.000
2017년 승인0.7330.0000.9590.9910.9981.0000.9980.9980.9590.9980.9590.959
2018년 신청0.7820.0001.0000.9911.0000.9981.0001.0001.0001.0001.0001.000
2018년 승인0.7820.0001.0000.9911.0000.9981.0001.0001.0001.0001.0001.000
2019년 신청0.5130.1881.0001.0001.0000.9591.0001.0001.0001.0001.0001.000
2019년 승인0.7820.0001.0000.9911.0000.9981.0001.0001.0001.0001.0001.000
2020년 신청0.5130.1881.0001.0001.0000.9591.0001.0001.0001.0001.0001.000
2020년 승인0.5130.1881.0001.0001.0000.9591.0001.0001.0001.0001.0001.000
2023-12-12T09:18:49.989357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령구분
연령1.0000.000
구분0.0001.000
2023-12-12T09:18:50.403974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2016년 신청2016년 승인2017년 신청2017년 승인2018년 신청2018년 승인2019년 신청2019년 승인2020년 신청2020년 승인구분연령
2016년 신청1.0000.9970.9950.9960.9940.9940.9940.9940.9940.9930.3330.000
2016년 승인0.9971.0000.9920.9940.9910.9910.9910.9910.9910.9900.2640.000
2017년 신청0.9950.9921.0000.9960.9990.9990.9990.9990.9990.9980.4080.000
2017년 승인0.9960.9940.9961.0000.9940.9940.9940.9940.9940.9930.3610.000
2018년 신청0.9940.9910.9990.9941.0001.0001.0001.0001.0001.0000.4080.000
2018년 승인0.9940.9910.9990.9941.0001.0001.0001.0001.0001.0000.4080.000
2019년 신청0.9940.9910.9990.9941.0001.0001.0001.0001.0001.0000.3330.000
2019년 승인0.9940.9910.9990.9941.0001.0001.0001.0001.0001.0000.4080.000
2020년 신청0.9940.9910.9990.9941.0001.0001.0001.0001.0001.0000.3330.000
2020년 승인0.9930.9900.9980.9931.0001.0001.0001.0001.0001.0000.3330.000
구분0.3330.2640.4080.3610.4080.4080.3330.4080.3330.3331.0000.000
연령0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T09:18:46.034475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:18:46.243381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

구분연령2016년 신청2016년 승인2017년 신청2017년 승인2018년 신청2018년 승인2019년 신청2019년 승인2020년 신청2020년 승인
0전국10대1084105110661031985950958891767703
1전국20대8573813389578496112561075612790122121310612478
2전국30대13219121101240411393148771396416058151081601714911
3전국40대20718187511954417837221582048223149214372273320905
4전국50대31742285623108028101357503296738031349543604933102
5전국60대18122158052025017563241512147127467242222845725156
6전국70대 이상3794280347923371551043116535490367925415
7경상북도10대87858178827881756159
8경상북도20대805771857816106910221117107110891040
9경상북도30대1260117211121030128012071314124113351252
구분연령2016년 신청2016년 승인2017년 신청2017년 승인2018년 신청2018년 승인2019년 신청2019년 승인2020년 신청2020년 승인
11경상북도50대3132285830802838350432463513325933263085
12경상북도60대1819162519331696217619632746243027932519
13경상북도70대 이상346239449311460363687451626491
14구미시10대121255776665
15구미시20대69659186878696948479
16구미시30대126113120115132121128124162152
17구미시40대172154163147212195211191194179
18구미시50대279263253232307290293277284270
19구미시60대120108137124139128172166192179
20구미시70대 이상18152017181829243128